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+Voluptuous is a Python data validation library
+==============================================
+
+|Build Status| |Stories in Ready|
+
+Voluptuous, *despite* the name, is a Python data validation library. It
+is primarily intended for validating data coming into Python as JSON,
+YAML, etc.
+
+It has three goals:
+
+1. Simplicity.
+2. Support for complex data structures.
+3. Provide useful error messages.
+
+Contact
+-------
+
+Voluptuous now has a mailing list! Send a mail to
+` <mailto:voluptuous@librelist.com>`__ to subscribe. Instructions will
+follow.
+
+You can also contact me directly via `email <mailto:alec@swapoff.org>`__
+or `Twitter <https://twitter.com/alecthomas>`__.
+
+To file a bug, create a `new
+issue <https://github.com/alecthomas/voluptuous/issues/new>`__ on GitHub
+with a short example of how to replicate the issue.
+
+Show me an example
+------------------
+
+Twitter's `user search
+API <https://dev.twitter.com/docs/api/1/get/users/search>`__ accepts
+query URLs like:
+
+::
+
+ $ curl 'http://api.twitter.com/1/users/search.json?q=python&per_page=20&page=1
+
+To validate this we might use a schema like:
+
+.. code:: pycon
+
+ >>> from voluptuous import Schema
+ >>> schema = Schema({
+ ... 'q': str,
+ ... 'per_page': int,
+ ... 'page': int,
+ ... })
+
+This schema very succinctly and roughly describes the data required by
+the API, and will work fine. But it has a few problems. Firstly, it
+doesn't fully express the constraints of the API. According to the API,
+``per_page`` should be restricted to at most 20, defaulting to 5, for
+example. To describe the semantics of the API more accurately, our
+schema will need to be more thoroughly defined:
+
+.. code:: pycon
+
+ >>> from voluptuous import Required, All, Length, Range
+ >>> schema = Schema({
+ ... Required('q'): All(str, Length(min=1)),
+ ... Required('per_page', default=5): All(int, Range(min=1, max=20)),
+ ... 'page': All(int, Range(min=0)),
+ ... })
+
+This schema fully enforces the interface defined in Twitter's
+documentation, and goes a little further for completeness.
+
+"q" is required:
+
+.. code:: pycon
+
+ >>> from voluptuous import MultipleInvalid, Invalid
+ >>> try:
+ ... schema({})
+ ... raise AssertionError('MultipleInvalid not raised')
+ ... except MultipleInvalid as e:
+ ... exc = e
+ >>> str(exc) == "required key not provided @ data['q']"
+ True
+
+...must be a string:
+
+.. code:: pycon
+
+ >>> try:
+ ... schema({'q': 123})
+ ... raise AssertionError('MultipleInvalid not raised')
+ ... except MultipleInvalid as e:
+ ... exc = e
+ >>> str(exc) == "expected str for dictionary value @ data['q']"
+ True
+
+...and must be at least one character in length:
+
+.. code:: pycon
+
+ >>> try:
+ ... schema({'q': ''})
+ ... raise AssertionError('MultipleInvalid not raised')
+ ... except MultipleInvalid as e:
+ ... exc = e
+ >>> str(exc) == "length of value must be at least 1 for dictionary value @ data['q']"
+ True
+ >>> schema({'q': '#topic'}) == {'q': '#topic', 'per_page': 5}
+ True
+
+"per\_page" is a positive integer no greater than 20:
+
+.. code:: pycon
+
+ >>> try:
+ ... schema({'q': '#topic', 'per_page': 900})
+ ... raise AssertionError('MultipleInvalid not raised')
+ ... except MultipleInvalid as e:
+ ... exc = e
+ >>> str(exc) == "value must be at most 20 for dictionary value @ data['per_page']"
+ True
+ >>> try:
+ ... schema({'q': '#topic', 'per_page': -10})
+ ... raise AssertionError('MultipleInvalid not raised')
+ ... except MultipleInvalid as e:
+ ... exc = e
+ >>> str(exc) == "value must be at least 1 for dictionary value @ data['per_page']"
+ True
+
+"page" is an integer >= 0:
+
+.. code:: pycon
+
+ >>> try:
+ ... schema({'q': '#topic', 'per_page': 'one'})
+ ... raise AssertionError('MultipleInvalid not raised')
+ ... except MultipleInvalid as e:
+ ... exc = e
+ >>> str(exc)
+ "expected int for dictionary value @ data['per_page']"
+ >>> schema({'q': '#topic', 'page': 1}) == {'q': '#topic', 'page': 1, 'per_page': 5}
+ True
+
+Defining schemas
+----------------
+
+Schemas are nested data structures consisting of dictionaries, lists,
+scalars and *validators*. Each node in the input schema is pattern
+matched against corresponding nodes in the input data.
+
+Literals
+~~~~~~~~
+
+Literals in the schema are matched using normal equality checks:
+
+.. code:: pycon
+
+ >>> schema = Schema(1)
+ >>> schema(1)
+ 1
+ >>> schema = Schema('a string')
+ >>> schema('a string')
+ 'a string'
+
+Types
+~~~~~
+
+Types in the schema are matched by checking if the corresponding value
+is an instance of the type:
+
+.. code:: pycon
+
+ >>> schema = Schema(int)
+ >>> schema(1)
+ 1
+ >>> try:
+ ... schema('one')
+ ... raise AssertionError('MultipleInvalid not raised')
+ ... except MultipleInvalid as e:
+ ... exc = e
+ >>> str(exc) == "expected int"
+ True
+
+URL's
+~~~~~
+
+URL's in the schema are matched by using ``urlparse`` library.
+
+.. code:: pycon
+
+ >>> from voluptuous import Url
+ >>> schema = Schema(Url())
+ >>> schema('http://w3.org')
+ 'http://w3.org'
+ >>> try:
+ ... schema('one')
+ ... raise AssertionError('MultipleInvalid not raised')
+ ... except MultipleInvalid as e:
+ ... exc = e
+ >>> str(exc) == "expected a URL"
+ True
+
+Lists
+~~~~~
+
+Lists in the schema are treated as a set of valid values. Each element
+in the schema list is compared to each value in the input data:
+
+.. code:: pycon
+
+ >>> schema = Schema([1, 'a', 'string'])
+ >>> schema([1])
+ [1]
+ >>> schema([1, 1, 1])
+ [1, 1, 1]
+ >>> schema(['a', 1, 'string', 1, 'string'])
+ ['a', 1, 'string', 1, 'string']
+
+Validation functions
+~~~~~~~~~~~~~~~~~~~~
+
+Validators are simple callables that raise an ``Invalid`` exception when
+they encounter invalid data. The criteria for determining validity is
+entirely up to the implementation; it may check that a value is a valid
+username with ``pwd.getpwnam()``, it may check that a value is of a
+specific type, and so on.
+
+The simplest kind of validator is a Python function that raises
+ValueError when its argument is invalid. Conveniently, many builtin
+Python functions have this property. Here's an example of a date
+validator:
+
+.. code:: pycon
+
+ >>> from datetime import datetime
+ >>> def Date(fmt='%Y-%m-%d'):
+ ... return lambda v: datetime.strptime(v, fmt)
+
+.. code:: pycon
+
+ >>> schema = Schema(Date())
+ >>> schema('2013-03-03')
+ datetime.datetime(2013, 3, 3, 0, 0)
+ >>> try:
+ ... schema('2013-03')
+ ... raise AssertionError('MultipleInvalid not raised')
+ ... except MultipleInvalid as e:
+ ... exc = e
+ >>> str(exc) == "not a valid value"
+ True
+
+In addition to simply determining if a value is valid, validators may
+mutate the value into a valid form. An example of this is the
+``Coerce(type)`` function, which returns a function that coerces its
+argument to the given type:
+
+.. code:: python
+
+ def Coerce(type, msg=None):
+ """Coerce a value to a type.
+
+ If the type constructor throws a ValueError, the value will be marked as
+ Invalid.
+ """
+ def f(v):
+ try:
+ return type(v)
+ except ValueError:
+ raise Invalid(msg or ('expected %s' % type.__name__))
+ return f
+
+This example also shows a common idiom where an optional human-readable
+message can be provided. This can vastly improve the usefulness of the
+resulting error messages.
+
+Dictionaries
+~~~~~~~~~~~~
+
+Each key-value pair in a schema dictionary is validated against each
+key-value pair in the corresponding data dictionary:
+
+.. code:: pycon
+
+ >>> schema = Schema({1: 'one', 2: 'two'})
+ >>> schema({1: 'one'})
+ {1: 'one'}
+
+Extra dictionary keys
+^^^^^^^^^^^^^^^^^^^^^
+
+By default any additional keys in the data, not in the schema will
+trigger exceptions:
+
+.. code:: pycon
+
+ >>> schema = Schema({2: 3})
+ >>> try:
+ ... schema({1: 2, 2: 3})
+ ... raise AssertionError('MultipleInvalid not raised')
+ ... except MultipleInvalid as e:
+ ... exc = e
+ >>> str(exc) == "extra keys not allowed @ data[1]"
+ True
+
+This behaviour can be altered on a per-schema basis. To allow additional
+keys use ``Schema(..., extra=ALLOW_EXTRA)``:
+
+.. code:: pycon
+
+ >>> from voluptuous import ALLOW_EXTRA
+ >>> schema = Schema({2: 3}, extra=ALLOW_EXTRA)
+ >>> schema({1: 2, 2: 3})
+ {1: 2, 2: 3}
+
+To remove additional keys use ``Schema(..., extra=REMOVE_EXTRA)``:
+
+.. code:: pycon
+
+ >>> from voluptuous import REMOVE_EXTRA
+ >>> schema = Schema({2: 3}, extra=REMOVE_EXTRA)
+ >>> schema({1: 2, 2: 3})
+ {2: 3}
+
+It can also be overridden per-dictionary by using the catch-all marker
+token ``extra`` as a key:
+
+.. code:: pycon
+
+ >>> from voluptuous import Extra
+ >>> schema = Schema({1: {Extra: object}})
+ >>> schema({1: {'foo': 'bar'}})
+ {1: {'foo': 'bar'}}
+
+Required dictionary keys
+^^^^^^^^^^^^^^^^^^^^^^^^
+
+By default, keys in the schema are not required to be in the data:
+
+.. code:: pycon
+
+ >>> schema = Schema({1: 2, 3: 4})
+ >>> schema({3: 4})
+ {3: 4}
+
+Similarly to how extra\_ keys work, this behaviour can be overridden
+per-schema:
+
+.. code:: pycon
+
+ >>> schema = Schema({1: 2, 3: 4}, required=True)
+ >>> try:
+ ... schema({3: 4})
+ ... raise AssertionError('MultipleInvalid not raised')
+ ... except MultipleInvalid as e:
+ ... exc = e
+ >>> str(exc) == "required key not provided @ data[1]"
+ True
+
+And per-key, with the marker token ``Required(key)``:
+
+.. code:: pycon
+
+ >>> schema = Schema({Required(1): 2, 3: 4})
+ >>> try:
+ ... schema({3: 4})
+ ... raise AssertionError('MultipleInvalid not raised')
+ ... except MultipleInvalid as e:
+ ... exc = e
+ >>> str(exc) == "required key not provided @ data[1]"
+ True
+ >>> schema({1: 2})
+ {1: 2}
+
+Optional dictionary keys
+^^^^^^^^^^^^^^^^^^^^^^^^
+
+If a schema has ``required=True``, keys may be individually marked as
+optional using the marker token ``Optional(key)``:
+
+.. code:: pycon
+
+ >>> from voluptuous import Optional
+ >>> schema = Schema({1: 2, Optional(3): 4}, required=True)
+ >>> try:
+ ... schema({})
+ ... raise AssertionError('MultipleInvalid not raised')
+ ... except MultipleInvalid as e:
+ ... exc = e
+ >>> str(exc) == "required key not provided @ data[1]"
+ True
+ >>> schema({1: 2})
+ {1: 2}
+ >>> try:
+ ... schema({1: 2, 4: 5})
+ ... raise AssertionError('MultipleInvalid not raised')
+ ... except MultipleInvalid as e:
+ ... exc = e
+ >>> str(exc) == "extra keys not allowed @ data[4]"
+ True
+
+.. code:: pycon
+
+ >>> schema({1: 2, 3: 4})
+ {1: 2, 3: 4}
+
+Recursive schema
+~~~~~~~~~~~~~~~~
+
+There is no syntax to have a recursive schema. The best way to do it is
+to have a wrapper like this:
+
+.. code:: pycon
+
+ >>> from voluptuous import Schema, Any
+ >>> def s2(v):
+ ... return s1(v)
+ ...
+ >>> s1 = Schema({"key": Any(s2, "value")})
+ >>> s1({"key": {"key": "value"}})
+ {'key': {'key': 'value'}}
+
+Extending an existing Schema
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Often it comes handy to have a base ``Schema`` that is extended with
+more requirements. In that case you can use ``Schema.extend`` to create
+a new ``Schema``:
+
+.. code:: pycon
+
+ >>> from voluptuous import Schema
+ >>> person = Schema({'name': str})
+ >>> person_with_age = person.extend({'age': int})
+ >>> sorted(list(person_with_age.schema.keys()))
+ ['age', 'name']
+
+The original ``Schema`` remains unchanged.
+
+Objects
+~~~~~~~
+
+Each key-value pair in a schema dictionary is validated against each
+attribute-value pair in the corresponding object:
+
+.. code:: pycon
+
+ >>> from voluptuous import Object
+ >>> class Structure(object):
+ ... def __init__(self, q=None):
+ ... self.q = q
+ ... def __repr__(self):
+ ... return '<Structure(q={0.q!r})>'.format(self)
+ ...
+ >>> schema = Schema(Object({'q': 'one'}, cls=Structure))
+ >>> schema(Structure(q='one'))
+ <Structure(q='one')>
+
+Allow None values
+~~~~~~~~~~~~~~~~~
+
+To allow value to be None as well, use Any:
+
+.. code:: pycon
+
+ >>> from voluptuous import Any
+
+ >>> schema = Schema(Any(None, int))
+ >>> schema(None)
+ >>> schema(5)
+ 5
+
+Error reporting
+---------------
+
+Validators must throw an ``Invalid`` exception if invalid data is passed
+to them. All other exceptions are treated as errors in the validator and
+will not be caught.
+
+Each ``Invalid`` exception has an associated ``path`` attribute
+representing the path in the data structure to our currently validating
+value, as well as an ``error_message`` attribute that contains the
+message of the original exception. This is especially useful when you
+want to catch ``Invalid`` exceptions and give some feedback to the user,
+for instance in the context of an HTTP API.
+
+.. code:: pycon
+
+ >>> def validate_email(email):
+ ... """Validate email."""
+ ... if not "@" in email:
+ ... raise Invalid("This email is invalid.")
+ ... return email
+ >>> schema = Schema({"email": validate_email})
+ >>> exc = None
+ >>> try:
+ ... schema({"email": "whatever"})
+ ... except MultipleInvalid as e:
+ ... exc = e
+ >>> str(exc)
+ "This email is invalid. for dictionary value @ data['email']"
+ >>> exc.path
+ ['email']
+ >>> exc.msg
+ 'This email is invalid.'
+ >>> exc.error_message
+ 'This email is invalid.'
+
+The ``path`` attribute is used during error reporting, but also during
+matching to determine whether an error should be reported to the user or
+if the next match should be attempted. This is determined by comparing
+the depth of the path where the check is, to the depth of the path where
+the error occurred. If the error is more than one level deeper, it is
+reported.
+
+The upshot of this is that *matching is depth-first and fail-fast*.
+
+To illustrate this, here is an example schema:
+
+.. code:: pycon
+
+ >>> schema = Schema([[2, 3], 6])
+
+Each value in the top-level list is matched depth-first in-order. Given
+input data of ``[[6]]``, the inner list will match the first element of
+the schema, but the literal ``6`` will not match any of the elements of
+that list. This error will be reported back to the user immediately. No
+backtracking is attempted:
+
+.. code:: pycon
+
+ >>> try:
+ ... schema([[6]])
+ ... raise AssertionError('MultipleInvalid not raised')
+ ... except MultipleInvalid as e:
+ ... exc = e
+ >>> str(exc) == "not a valid value @ data[0][0]"
+ True
+
+If we pass the data ``[6]``, the ``6`` is not a list type and so will
+not recurse into the first element of the schema. Matching will continue
+on to the second element in the schema, and succeed:
+
+.. code:: pycon
+
+ >>> schema([6])
+ [6]
+
+Running tests.
+--------------
+
+Voluptuous is using nosetests:
+
+::
+
+ $ nosetests
+
+Why use Voluptuous over another validation library?
+---------------------------------------------------
+
+**Validators are simple callables**
+ No need to subclass anything, just use a function.
+**Errors are simple exceptions.**
+ A validator can just ``raise Invalid(msg)`` and expect the user to
+ get useful messages.
+**Schemas are basic Python data structures.**
+ Should your data be a dictionary of integer keys to strings?
+ ``{int: str}`` does what you expect. List of integers, floats or
+ strings? ``[int, float, str]``.
+**Designed from the ground up for validating more than just forms.**
+ Nested data structures are treated in the same way as any other
+ type. Need a list of dictionaries? ``[{}]``
+**Consistency.**
+ Types in the schema are checked as types. Values are compared as
+ values. Callables are called to validate. Simple.
+
+Other libraries and inspirations
+--------------------------------
+
+Voluptuous is heavily inspired by
+`Validino <http://code.google.com/p/validino/>`__, and to a lesser
+extent, `jsonvalidator <http://code.google.com/p/jsonvalidator/>`__ and
+`json\_schema <http://blog.sendapatch.se/category/json_schema.html>`__.
+
+I greatly prefer the light-weight style promoted by these libraries to
+the complexity of libraries like FormEncode.
+
+.. |Build Status| image:: https://travis-ci.org/alecthomas/voluptuous.png
+ :target: https://travis-ci.org/alecthomas/voluptuous
+.. |Stories in Ready| image:: https://badge.waffle.io/alecthomas/voluptuous.png?label=ready&title=Ready
+ :target: https://waffle.io/alecthomas/voluptuous
generated by cgit v1.2.3 (git 2.26.2) at 2024-11-12 22:49:40 +0000